class_docstr: Default neural network module used in `Neural` mixer to learn the predictive task based on encoded feature representations.
  
  Small architecture with either a one or two linear layers. Hidden size might be constrained to have at most `max_params` in the network, trading off accuracy for speed.
code: def forward(self, input):
      try:
          with LightwoodAutocast():
              output = self.net(input)
      except Exception:
          output = self.net(input)
      return output
  
file_path: lightwood/lightwood/mixer/helpers/default_net.py
imports: import math
  import torch
  from lightwood.helpers.torch import LightwoodAutocast
  from lightwood.helpers.device import get_device_from_name
  from lightwood.helpers.log import log
  import numpy
label_desc: Use image node_id 3 for calling the DefaultNet obj's underlying member method code with example usage: obj.forward(input) and returns: output